Identification of key genes and small molecule drugs in osteoarthritis by integrated bioinformatics analysis

BACKGROUND: Osteoarthritis (OA) is a common joint degenerative disease that can affect multiple joints. Genetic events may play an important regulatory role in the early stages of the disease, but the specific mechanisms have not yet been fully elucidated. The main purpose of this study was to screen for disease-causing hub genes and effective small molecule drugs to reveal the pathogenesis of OA and to develop novel drugs for treatment. METHODS: Two gene expression profile datasets, GSE55235 and GSE55457, were integrated and further analyzed. The consistently differentially expressed genes (DEGs) were identified, and functional annotation and pathway analysis of these genes were performed with GO and KEGG. A protein–protein interaction network (PPI) of the DEGs was generated using STRING, and potential small molecule drug screening was performed on the connectivity map (CMap). RESULTS: A total of 158 consistently differentially expressed genes were identified from the two profile datasets. The functions of these DEGs are mainly related to the TNF signaling pathway, osteoclast differentiation, MAPK signaling pathway and so on. The PPI network contains 127 nodes and 1802 edges, and the ten hub genes were interleukin 6 (IL6), vascular endothelial growth factor A (VEGFA)and so on. 7 small molecule drugs were identified as potential interactors with these hubs. CONCLUSIONS: This study explains the disorder of expression in the pathological process of OA at transcriptome, which will help to understand the pathogenesis of OA.